17 citations as recorded by crossref.

1. Assessing the clear-sky assimilation of FY-3D/HIRAS water vapor data and its impact on Typhoon forecasting X. Xu et al. https://doi.org/10.1016/j.atmosres.2025.108684
2. Region and cloud regime dependence of parametric sensitivity in E3SM atmosphere model Y. Qian et al. https://doi.org/10.1007/s00382-023-06977-3
3. Ensemble prediction using a new dataset of ECMWF initial states – OpenEnsemble 1.0 P. Ollinaho et al. https://doi.org/10.5194/gmd-14-2143-2021
4. Parametric Sensitivity and Uncertainty Quantification in the Version 1 of E3SM Atmosphere Model Based on Short Perturbed Parameter Ensemble Simulations Y. Qian et al. https://doi.org/10.1029/2018JD028927
5. Assimilation of Hyperspectral Infrared Atmospheric Sounder Data of FengYun-3E Satellite and Assessment of Its Impact on Analyses and Forecasts R. Liu et al. https://doi.org/10.3390/rs16050908
6. Simulating model uncertainty of subgrid-scale processes by sampling model errors at convective scales M. Van Ginderachter et al. https://doi.org/10.5194/npg-27-187-2020
7. Constraining stochastic parametrisation schemes using high‐resolution simulations H. Christensen https://doi.org/10.1002/qj.3717
8. Efficient Bayesian inference for large chaotic dynamical systems S. Springer et al. https://doi.org/10.5194/gmd-14-4319-2021
9. Physical characteristics of frozen hydrometeors inferred with parameter estimation A. Geer https://doi.org/10.5194/amt-14-5369-2021
10. Climate model tuning with adaptive supermodeling J. Seneca et al. https://doi.org/10.1063/5.0304768
11. Optimization of NWP model closure parameters using total energy norm of forecast error as a target P. Ollinaho et al. https://doi.org/10.5194/gmd-7-1889-2014
12. A Posteriori Learning for Quasi‐Geostrophic Turbulence Parametrization H. Frezat et al. https://doi.org/10.1029/2022MS003124
13. Model Uncertainty Representation in a Convection-Permitting Ensemble—SPP and SPPT in HarmonEPS I. Frogner et al. https://doi.org/10.1175/MWR-D-21-0099.1
14. Calibrating climate models using inverse methods: case studies with HadAM3, HadAM3P and HadCM3 S. Tett et al. https://doi.org/10.5194/gmd-10-3567-2017
15. Online identification of large-scale chaotic system V. Shemyakin & H. Haario https://doi.org/10.1007/s11071-018-4239-5
16. Optimizing convection‐permitting ensemble via selection of the coarse ensemble driving members P. Khain et al. https://doi.org/10.1002/met.2137
17. Stochastic and Perturbed Parameter Representations of Model Uncertainty in Convection Parameterization* H. Christensen et al. https://doi.org/10.1175/JAS-D-14-0250.1